System and Method for Next Object Prediction for Ics Flow Using Artificial Intelligence/Machine Learning

1. A system for next step object for ICS (integration cloud services) flow using artificial intelligence/machine learning, comprising: a computer including one or more microprocessors; an integration platform running on the computer, the integration platform comprising an integration flow designer, the integration flow designer having access to a library stored at a database, the library comprising a plurality of objects, each object for use within an integration flow designed within the integration flow designer; wherein the computer is configured to perform a method comprising: starting a design template for an integration flow within the integration flow designer, the integration flow comprising a first flow file; receiving an indication of a first object to be utilized within the integration flow within the integration flow designer, the first object being selected from the library comprising the plurality of objects, the first object comprising a connection to an instance of an application external to the integration flow, the first object being associated with a definition and a configuration provided by a source component associated with the first object and defined and stored within the integration platform; collecting user context, the user context relating to the integration flow within the integration flow designer; displaying, via a graphical user interface, a plurality of ranked potential next object predictions for use within the integration flow within the integration flow designer based on the collected user context and the first object to be utilized within the integration flow, wherein the collected user context is utilized in querying a hierarchical clustering model of invariant pattern recognition of process models to determine the plurality of potential next object predictions, the hierarchical clustering model utilizing stored machine learning knowledge of process design as a hierarchy of clusters of process models, wherein each of the plurality of ranked potential next object predictions is associated with a definition and a configuration provided by a target component of a plurality of target components, each of the definitions and configuration associated with each of the plurality of ranked potential next object predictions being defined and stored within the integration platform, wherein each of the plurality of potential next object predictions comprise one of an application, an operation, and a business object, wherein the plurality of potential next object predictions are contained within the library stored at the database, wherein the potential next object predictions are ranked according to a determination made, based upon the collected user context, of a plurality of other integration flows each comprising the first object, wherein the plurality of other integration flows comprise a plurality of other flow files stored at the integration platform; wherein each of the flow file and the plurality of other flow files comprise one or more objects, arrays, string fields, or numeric fields; wherein the plurality of other integration flows is determined based upon a determination of structural and semantic similarities between the flow file and the plurality of other flow files, said determination of structural and semantic similarities comprising generating a similarity score for each string field, numeric field, and array of the flow file as compared to the plurality of other flow files; receiving an indication of a rejection of one of the plurality of ranked potential next object predictions; updating the display at the graphical user interface of the plurality of ranked potential next object predictions to remove from the display the rejected one of the plurality of ranked potential next objects predictions and displaying a next highest ranked next object prediction; receiving an indication of a selection of a selected potential next object prediction of the updated display of the plurality of ranked potential next step predictions.

2. The system of claim 1, wherein user context takes into account the organization, subsidiary, department, sub-departments, and user information.

3. The system of claim 1, wherein a ranking generator is used in providing the plurality of potential next object predictions.

4. The system of claim 3, wherein the ranking generator utilizes an input pattern to rank a plurality of output patterns matched with the input pattern, the ranking utilizing one or more inputs; and wherein the input pattern is created in part from the collected user context.

5. A method for next object prediction for ICS (integration cloud services) flow using artificial intelligence/machine learning, comprising: providing a computer that includes one or more microprocessors; providing an integration platform running on the computer, the integration platform comprising an integration flow designer, the integration flow designer having access to a library stored at a database, the library comprising a plurality of objects, each object for use within an integration flow designed within the integration flow designer; starting a design template for an integration flow within the integration flow designer; receiving an indication of a first object to be utilized within the integration flow within the integration flow designer, the first object being selected from the library comprising the plurality of objects, the first object comprising a connection to an instance of an application external to the integration flow, the first object being associated with a definition and a configuration provided by a source component associated with the first object and defined and stored within the integration platform; collecting user context, the user context relating to the integration flow within the integration flow designer; displaying, via a graphical user interface, a plurality of ranked potential next object predictions for use within the integration flow within the integration flow designer based on the collected user context and the first object to be utilized within the integration flow, wherein the collected user context is utilized in querying a hierarchical clustering model of invariant pattern recognition of process models to determine the plurality of potential next object predictions, the hierarchical clustering model utilizing stored machine learning knowledge of process design as a hierarchy of clusters of process models, wherein each of the plurality of ranked potential next object predictions is associated with a definition and a configuration provided by a target component of a plurality of target components, each of the definitions and configuration associated with each of the plurality of ranked potential next object predictions being defined and stored within the integration platform, wherein each of the plurality of potential next object predictions comprise one of an application, an operation, and a business object, wherein the plurality of potential next object predictions are contained within the library stored at the database, wherein the potential next object predictions are ranked according to a determination made, based upon the collected user context, of a plurality of other integration flows each comprising the first object, wherein the plurality of other integration flows comprise a plurality of other flow files stored at the integration platform; wherein each of the flow file and the plurality of other flow files comprise one or more objects, arrays, string fields, or numeric fields; wherein the plurality of other integration flows is determined based upon a determination of structural and semantic similarities between the flow file and the plurality of other flow files, said determination of structural and semantic similarities comprising generating a similarity score for each string field, numeric field, and array of the flow file as compared to the plurality of other flow files; receiving an indication of a rejection of one of the plurality of ranked potential next object predictions; updating the display at the graphical user interface of the plurality of ranked potential next object predictions to remove from the display the rejected one of the plurality of ranked potential next objects predictions and displaying a next highest ranked next object prediction; and receiving an indication of a selection of a selected potential next object prediction of the plurality of ranked next step predictions.

6. The method of claim 5, wherein user context takes into account the organization, subsidiary, department, sub-departments, and user information.

7. The method of claim 5, wherein a ranking generator is used in providing the plurality of potential next object predictions.

8. The method of claim 7, wherein the ranking generator utilizes an input pattern to rank a plurality of output patterns matched with the input pattern, the ranking utilizing one or more inputs; and wherein the input pattern is created in part from the collected user context.

9. A non-transitory computer readable storage medium, having instructions for next step prediction for ICS (integration cloud services) flow using artificial intelligence/machine learning, which when read and executed by one or more computers cause the one or more computers to perform a method comprising: providing, at the one or more computers, each of the one or more computers comprising one or more microprocessors, an integration platform running on the computer, the integration platform comprising an integration flow designer, the integration flow designer having access to a library stored at a database, the library comprising a plurality of objects, each object for use within an integration flow designed within the integration flow designer; starting a design template for an integration flow within the integration flow designer; receiving an indication of a first object to be utilized within the integration flow within the integration flow designer, the first object being selected from the library comprising the plurality of objects, the first object comprising a connection to an instance of an application external to the integration flow, the first object being associated with a definition and a configuration provided by a source component associated with the first object and defined and stored within the integration platform; collecting user context, the user context relating to the integration flow within the integration flow designer; displaying, via a graphical user interface, a plurality of ranked potential next object predictions for use within the integration flow within the integration flow designer based on the collected user context and the first object to be utilized within the integration flow, wherein the collected user context is utilized in querying a hierarchical clustering model of invariant pattern recognition of process models to determine the plurality of potential next object predictions, the hierarchical clustering model utilizing stored machine learning knowledge of process design as a hierarchy of clusters of process models, wherein each of the plurality of ranked potential next object predictions is associated with a definition and a configuration provided by a target component of a plurality of target components, each of the definitions and configuration associated with each of the plurality of ranked potential next object predictions being defined and stored within the integration platform, wherein each of the plurality of potential next object predictions comprise one of an application, an operation, and a business object, wherein the plurality of potential next object predictions are contained within the library stored at the database, wherein the potential next object predictions are ranked according to a determination made, based upon the collected user context, of a plurality of other integration flows each comprising the first object, wherein the plurality of other integration flows comprise a plurality of other flow files stored at the integration platform; wherein each of the flow file and the plurality of other flow files comprise one or more objects, arrays, string fields, or numeric fields; wherein the plurality of other integration flows is determined based upon a determination of structural and semantic similarities between the flow file and the plurality of other flow files, said determination of structural and semantic similarities comprising generating a similarity score for each string field, numeric field, and array of the flow file as compared to the plurality of other flow files; receiving an indication of a rejection of one of the plurality of ranked potential next object predictions; updating the display at the graphical user interface of the plurality of ranked potential next object predictions to remove from the display the rejected one of the plurality of ranked potential next objects predictions and displaying a next highest ranked next object prediction; and receiving an indication of a selection of a selected potential next object prediction of the plurality of ranked next step predictions.

10. The non-transitory computer readable storage medium of claim 9, wherein user context takes into account the organization, subsidiary, department, sub-departments, and user information.

11. The non-transitory computer readable storage medium of claim 9, wherein a ranking generator is used in providing the plurality of potential next object predictions; wherein the ranking generator utilizes an input pattern to rank a plurality of output patterns matched with the input pattern, the ranking utilizing one or more inputs; and wherein the input pattern is created in part from the collected user context.